Decision support systems (DSS) have been developed to efficiently retrieve selected information from data warehouses, thereby providing business intelligence information to the organization. One type of decision support system is known as an on-line analytical processing system (“OLAP”). In general, OLAP systems analyze the data from a number of different perspectives and support complex analyses against large input data sets.
In conventional web-based OLAP access systems, the exchange of business intelligence information between World Wide Web client computer systems and business intelligence server computer systems requires substantial processing capabilities and resources on the individual client computer systems. Often, the interface between the client and the server systems require the client systems to download, install and run a plurality of web browser plugin utilities in order to view or effectively interact with the exchanged information. By requiring the client-side systems to perform a substantial portion of the information processing, server-side applications were able to effectively manipulate the large quantities of data typically in business intelligence or OLAP environments. However, the ever changing landscape of browser and plugin software (e.g., java) makes it difficult for client-side systems to remain current with every element of technology necessary to interact with the server-side applications providing the business intelligent information. Further, for individuals who routinely use more than one client-side machine to access information, ensuring that each machine includes all required elements is difficult and sometimes impossible
Accordingly, existing business intelligence systems fail to provide a method and system for exchanging business intelligence information over a computer network wherein client-side processing and software requirements are reduced to a level compatible with virtually all client-side systems.